使用具有磁流体动力(MHD)和滑移效应的非牛顿纳米流体对叶片涂层工艺(NIS-BCP)进行非等温机器学习研究

Muhammad Asif Javed, Abuzar Ghaffari, H M Atif, Ahmed S Sowayan, Sami Ullah Khan
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引用次数: 0

摘要

相关研究报告了叶片涂层过程中磁流体动力学(MHD)和非线性滑移系数对腹板/基板涂层厚度的影响。在流体动力学基本方程的帮助下,使用非牛顿纳米流体模型对叶片涂层过程进行了二维分析。首先,利用缩放因子将运动方程(EOM)系统转换为非二维形式。其次,借助润滑近似理论(LAT)进一步简化模型方程。由此产生的边界值问题被转换成流函数,以消除流动方程中的压力梯度,然后使用 Matlab 内置函数 bvp4c 和假位置法(Regula-Falsi 法)进行数值处理。数值数据与人工神经网络(ANN)模拟结果的对比研究发现,两者的结果非常吻合。通过图形表示法研究了各种参数对物理量的影响。结果表明,在叶片涂层流动过程中,磁流体力学(MHD)、纳米颗粒和滑移效应的影响不容忽视,因为这些参数对速度、温度、压力、涂层厚度、叶片载荷和流线都有显著影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine learning non-isothermal study of the blade coating process (NIS-BCP) using non-Newtonian nanofluid with magnetohydrodynamic (MHD) and slip effects
The underlying investigation reports the effects of the magnetohydrodynamics (MHD) and non-linear slip coefficients on the coating thickness of the web/substrate during the blade coating process. Two dimensional analysis of the blade coating process is performed using non-Newtonian nanofluid model with the help of basic equations of fluid dynamics are performed. Firstly, the system of equations of motion (EOM) is transformed into the non-dimensional form by using the scaling factors. Secondly, the modeled equations are further simplified with the help of lubrication approximation theory (LAT). The resulting boundary value problem is transformed into stream function to eliminate the pressure gradient from the flow equation and then numerically tackled with the Matlab built-in function bvp4c with the method of false position (Regula-Falsi Method). A comparative study of numerical data with results simulated by artificial neural networks (ANN) found that results are in excellent agreement. The impact of sundry parameters on physical quantities is examined through graphical representation. Results indicate that the influence of magnetohydrodynamics (MHD), nanoparticle and slip effects cannot be ignored during the blade coating flow, as a significant impact of these parameters is observed on velocity, temperature, pressure, coating thickness, blade load, and streamlines.
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